OPTIMIZING SPEECH RECOGNITION FOR CHILDREN WITH HEARING LOSS

优化听力损失儿童的语音识别

• 批准号: 8492061
• 负责人: Ryan W. McCreery
• 金额: $ 13.87万
• 依托单位: FATHER FLANAGAN'S BOYS' HOME
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-18 至 2015-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8492061
• 关键词: Accounting; Adult; Affect; Auditory; Characteristics; Child; Clinical; Cognitive; Communication; Data; Development; Elderly; Frequencies; Goals; Hearing; Hearing Aids; Human; Individual; Intervention; Knowledge; Language; Language Delays; Lead; Linguistics; Measures; Memory; Mission; Modeling; Noise; Outcome; Performance; Process; Public Health; Research; Short-Term Memory; Speech; Speech Delay; Speech Intelligibility; Speech Perception; Testing; Work; base; clinical application; computerized data processing; digital; disability; hearing impairment; improved; indexing; innovation; memory process; memory recognition; programs; skills; speech recognition; theories

DESCRIPTION (provided by applicant): Current approaches to quantifying audibility and predicting speech recognition for children are based on adult data, and consequently, overestimate performance for children and underestimate the amount of audibility that is necessary to achieve high levels of understanding. Although differences in speech recognition between adults and children have been widely studied, lack of research examining how such differences impact audibility-based predictions of speech recognition limits the clinical application of these findings. Furthermore, the accuracy of such predictions with children is presently inadequate. The long-term goal of this research is to enhance speech and language outcomes in children with HL by improving Speech Intelligibility Index (SII) predictions of speech recognition. More accurate estimates of speech recognition would promote optimization of amplification for children. An intermediate objective is to quantify the influence of language and immediate memory on predictions of speech recognition from the SII. To achieve this objective, speech recognition, receptive language, and immediate memory skills will be measured in children and used to generate transfer functions. The central hypothesis of this proposal is that adult-child differences and variability among children can be more accurately predicted by modifying the SII to account for children's linguistic ability and immediate memory, a hypothesis that is supported by preliminary data. This theory will be tested by pursuing three specific aims: 1) Determine the influence of linguistic abilities on audibility-based predictions of speech recognition in children with normal hearing (NH), 2) Determine the influence of immediate memory processes on audibility-based predictions of speech recognition in children with NH, and 3) Adapt the SII to more accurately predict speech recognition in children with HL by incorporating linguistic knowledge and immediate memory skills. In Aim 1, speech recognition and language abilities will be measured for a large group of children with normal hearing in order to determine if consideration of the listener's language knowledge can improve SII predictions of speech recognition. In Aim 2, speech recognition and immediate memory skills, including verbal and visuo-spatial measures of storage and storage with processing, will be measured for a large group of children with normal hearing to determine how these processes support speech recognition. In Aim 3, measures of language and immediate memory will be incorporated into SII transfer functions for a group of children with hearing loss to model how these factors affect unaided and aided speech understanding. The proposed research is expected to lead to optimization of amplification in children with hearing loss and a better understanding of how language and immediate memory influence speech recognition during development.

描述（由申请人提供）：目前量化儿童可听度和预测语音识别的方法是基于成人数据，因此高估了儿童的表现，并低估了实现高水平理解所需的可听度。尽管成人和儿童之间语音识别的差异已得到广泛研究，但缺乏研究这些差异如何影响基于听觉的语音识别预测，限制了这些发现的临床应用。此外，目前对儿童的此类预测的准确性还不够。这项研究的长期目标是通过改善语音识别的语音清晰度指数 (SII) 预测来增强 HL 儿童的言语和语言结果。对语音识别的更准确估计将促进儿童放大效果的优化。中间目标是量化语言和即时记忆对 SII 语音识别预测的影响。为了实现这一目标，将测量儿童的语音识别、接受性语言和即时记忆技能，并用于生成传递函数。该提案的中心假设是，通过修改 SII 以考虑儿童的语言能力和即时记忆，可以更准确地预测成人与儿童的差异和儿童之间的变异性，这一假设得到了初步数据的支持。该理论将通过追求三个具体目标进行测试：1）确定语言能力对听力正常（NH）儿童基于可听性的语音识别预测的影响，2）确定即时记忆过程对 NH 儿童基于可听性的语音识别预测的影响，以及 3）通过结合语言知识和即时记忆技能，调整 SII 以更准确地预测 HL 儿童的语音识别。在目标 1 中，将对一大群听力正常的儿童进行语音识别和语言能力测量，以确定考虑听者的语言知识是否可以改善语音识别的 SII 预测。在目标 2 中，将对一大群听力正常的儿童进行语音识别和即时记忆技能的测量，包括言语和视觉空间的存储测量以及存储与处理，以确定这些过程如何支持语音识别。在目标 3 中，语言和即时记忆的测量将被纳入一组听力损失儿童的 SII 传递函数中，以模拟这些因素如何影响无辅助和辅助言语理解。拟议的研究预计将优化听力损失儿童的扩音能力，并更好地理解语言和即时记忆如何影响发育过程中的语音识别。